In March, I have published a linked view display with a population cartogram of Switzerland (in German, in French). The occasion was a federal poll that convinced the majority of the voting population but didn’t gain support in enough many cantons. The cartogram has sparked quite some interest and I have covered its conceptualisation as … Continue reading Reworked versions of my hexagonal population cartogram
… is the title of my most recent project. It’s a bit artsy, but I think some of the concepts behind it may also have practical applications in this world of ever more abundant webcam footage (maybe need to think a bit more on this point later).
In Zurich Sky, I destilled yearly aggregates of the sky over Zurich Switzerland. I did this by first scraping tons of images from the website of the Swiss domain registrar SWITCH. They have two webcams, one in Zurich one in the Alps, whose images are publicly accessible in their archive (thanks!).
Zurich Sky: Web-scraped sky colour over Zurich, Switzerland
The SWITCH archive features one image every hour. Luckily for my project, the URLs of the individual pictures adhere to a nice structured format which makes automatic downloading of several thousand images rather easy. An example is here:
Some weeks ago I visualised the Swiss cantons (states) and their population numbers using what information visualization scientists call a linked view. You can click through to the actual, interactive visualization: here in German or here in French. In what follows I want to give a bit more detail about what led to this visualization and what conceptual thinking went into the design.
In a subsequent post I will also describe the toolset I used to produce this visualization, so that you can build your own. If you’re not interested in the Background, you can skip to the Conceptually section. If that’s neither your cup of tea and you’re here primarily because you want to know how to produce such a visualization yourself, you’ll unfortunately have to patience yourself and wait for the second part of this series (it’s here!).
Background
Why population sizes matter – in such a small country
Why is the particular piece of information that is visualised here important or interesting? Well, in the Swiss political system cantons are represented at the federal level, whereas cities aren’t. However, some of the big cities represent a considerably larger number of people than quite some of the smaller cantons. There have been many debates if and how cities ought to be represented in the political system, about the specificity of urban issues and how those are dealt with or ignored in Swiss politics and if weighting of the cantons should be adapted to better match their population size. The issue crops up both in relation to elections and polls (Switzerland having a direct democracy there are really many of the latter).
Cartogram on Swiss TV
When I published the visualization Switzerland has just held such a poll. The poll did not pass, it achieved only 54.3% of “yes” votes.
– Wait, what? Yep, the vote won a solid majority of the people, but too many cantons said “nay” and thus, by the rules, it was a “nay”. Now, one can argue that this is not sensible or that it is perfectly sensible, I’m not going to do this here. But this background means, to my pleasure, that the visualisation was able to spark and inform many discussions (and met quite an audience). To my big surprise, it was even briefly featured in nation-wide primetime news, in a slightly reworked version. Continue reading “Conceptualisation of a D3 linked view with a hexagonal cartogram”
After my project proposal had been accepted, I have attended a workshop at ETH Zurich, titled “Cartography & Narratives” organised by Barbara Piatte, Sébastien Caquard and Anne-Kathrin Reuschel in last summer. The goal of the workshop was to explore “mapping as a conceptual framework to improve our understating of narratives”. Narratives are “an expression in discourse of … Continue reading Flickr as a vehicle of narrative: photos contextualised in space and time
The Swiss population has grown more or less steadily over the last decades: With a current growth of about 1%, the Federal Statistics Office has forecast that Switzerland should have welcomed the 8 millionth inhabitant at some point this summer (jeez, I remember learning at school that Switzerland has 6.5 mio. inhabitants – you can … Continue reading Swiss population density versus that of cities
I’ve recently been playing with D3.js, mainly for my side-project, SoMePolis, which investigates social media usage by Swiss MPs. D3.js (D3: data-driven documents) is a Javascript library for creating complex, static or animated/interactive web graphics using HTML, SVG and CSS. The main site has a short tutorial and lots of example implementations. A well-known solid introduction to … Continue reading Visualizing Swiss politicians on Twitter using D3.js
[Deutsch weiter unten] Recently, I’ve been looking into analysis and visualization of Twitter networks. So, David Bauer posting a list of 300+ German-speaking, Twitter-using journalists came just right. Scroll down to see the resulting network. By they way, you can find more information on the technical background of the production of these Twitter network visualizations in this post. [German] … Continue reading Journalists’ Twitter network
[Deutsch weiter unten] Recently, I’ve been working on a Twitter-related project with two friends of mine. As there’s nothing to present yet, I won’t go into detail regarding that project. But working on Twitter-related stuff led me to explore the generation, modelling, analysis and visualization of Twitter networks. Then, some weeks back, Swiss journalist/author/blogger David … Continue reading Twitter networks – Mechanics
“Einigkeit und Recht und Frei-ei-heit…!” But before we get to that, as explained earlier, there are different levels in my ZIPScribble Maps: Level 1 ZIPScribble Map: Only the first digit of the postcode is compared. Thus, a discontinuity is detected, for example, between postal codes 8679 and 9000, but no discontinuity is detected between 8399 and 8400. … Continue reading ZIPScribble Map Germany
“Allons enfants de la patrie…!” But before we get to that, as explained earlier, there are different levels in my ZIPScribble Maps: Level 1 ZIPScribble Map: Only the first digit of the postcode is compared. Thus, a discontinuity is detected, for example, between postal codes 8679 and 9000, but no discontinuity is detected between 8399 and 8400. … Continue reading ZIPScribble Map France
Earlier I’ve blogged a two-parts tutorial on how to create ZIPScribble Maps using the Processing visualization framework. The map uses a background I made with TileMill and CC-BY-licensed postcode data from the Geonames gazetteer portal. (By the way, here’s an informative short TileMill tutorial by Pierre La Baume) As explained earlier, there are different levels … Continue reading ZIPScribble Map Italy
(as can be seen from 
